The SQL SELECT statement is possibly the most commonly used SQL statement. It’s often used to return data from a database, but it can also be used to call functions that return data. The SELECT statement can also be used to return static values, such as string literals.
But the SELECT statement isn’t the only way we can return data in SQL. Another way to return values is with the VALUES statement.
Primary keys are a crucial part of relational database management systems (RDBMSs). Most of the time we create a primary key constraint against a single column that is the unique identifier for the table.
But we can also create primary key constraints against more than one column. When we do this, we call it a composite primary key.
Composite keys can be handy when we don’t have a single column that contains unique values, but multiple columns can be combined to create a unique value.
Most of the major RDBMSs provide us with the ability to perform set operations.
A set operation is one that combines the results of multiple query blocks into one. For example, we could combine the result of two separate SELECT statements. The results are displayed in a single result set as though we’d run a single query.
With SQL we can use various methods to check whether or not a table (or other object) exists in the database. The method we use will often depend on the RDBMS we’re using, as well as the task we’re trying to undertake.
There’s usually a reason we’re trying to check for the existence of a table, and often the syntax we use will be tied to that reason. For example the ...IF EXISTS clause is a handy addition to the DROP TABLE statement, and the ...IF NOT EXISTS clause can often be used with the CREATE TABLE statement.
Other times we may simply want to see if the table exists without performing any immediate actions against that table. In such cases, we would need to run code specifically to see if the table exists.
Below are examples of code we can use in each of the above scenarios.
The SQL EXISTS predicate is used to specify a test for a non-empty set. It returns TRUE or FALSE, depending on the outcome of the test.
When we incorporate the EXISTS predicate operator into our SQL queries, we specify a subquery to test for the existence of rows. If there are any rows, then the subquery is TRUE. If there are no rows, then the subquery is FALSE.
In SQL, we can use the DROP TABLE IF EXISTS statement to drop a table only if it exists.
While it may seem obvious that we can only drop a table if it exists (i.e. we can’t drop a table that doesn’t exist), there’s a good reason for using this statement.
The reason we put an IF EXISTS clause into a DROP TABLE statement is to prevent any errors that would occur if the table doesn’t exist.
Sometimes when we run a SQL query, we only want to see unique rows. But depending on the columns we’re selecting, we might end up with duplicate rows. And this could happen without even knowing it, especially with large data sets.
But it doesn’t have to be this way.
Fortunately most SQL databases provide us with an easy way to remove duplicates.
The SQL COUNT() function is a handy tool for telling us how many rows would be returned in a query. We can pass a column name to the function or we can pass the asterisk (*) wildcard to indicate all columns.
If a column contains NULL values, we could get different results, depending on whether we use the column name or the asterisk (*).
The SQL UNION operator concatenates the results of two queries into a single result set. By default it returns distinct rows (i.e. it removes any redundant duplicate rows from the result set). But we can also use UNION ALL to return non-distinct rows (i.e. retain duplicates).
When it comes to NULL values, it’s pretty straight forward. SQL treats two NULL values as non distinct values. In other words, they’re duplicates.